4.7 Article

Epidemiology of child pedestrian casualty rates: Can we assume spatial independence?

期刊

ACCIDENT ANALYSIS AND PREVENTION
卷 37, 期 4, 页码 651-659

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.aap.2005.03.007

关键词

Bayesian; spatial modelling; child pedestrian; deprivation

向作者/读者索取更多资源

Child pedestrian injuries are often investigated by means of ecological studies, yet are clearly part of a complex spatial phenomena. Spatial dependence within such ecological analyses have rarely been assessed, yet the validity of basic statistical techniques rely on a number of independence assumptions. Recent work from Canada has highlighted the potential for modelling spatial dependence within data that was aggregated in terms of the number of road casualties who were resident in a given geographical area. Other jurisdictions aggregate data in terms of the number of casualties in the geographical area in which the collision took place. This paper contrasts child pedestrian casualty data from Devon County UK, which has been aggregated by both methods. A simple ecological model, with minimally useful covaraties relating to measures of child deprivation, provides evidence that data aggregated in terms of the casualty's home location cannot be assumed to be spatially independent and that for analysis of these data to be valid there must be some accounting for spatial auto-correlation within the model structure. Conversely, data aggregated in terms of the collision location (as is usual in the UK) was found to be spatially independent. Whilst the spatial model is clearly more complex it provided a superior fit to that seen with either collision aggregated or non-spatial models. Of more importance, the ecological level association between deprivation and casualty rate is much lower once the spatial structure is accounted for, highlighting the importance using appropriately structured models. (c) 2005 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据